November 2025

This study examined the organizational commitment of Bureau of Corrections officers at Iwahig Prison and Penal Farm in Puerto Princesa City, Palawan. It explored the relationship between work values, self-actualization, and job satisfaction, aiming to construct a structural equation model (SEM) to understand their collective influence on organizational commitment. The research design employed a quantitative, correlational approach, utilizing validated and pre-tested Likert-scale instruments to collect data from 522 officers through total enumeration sampling. The results revealed high levels of work values, self-actualization, and job satisfaction among the respondents, with significant positive correlations to organizational commitment. Job satisfaction emerged as the strongest predictor of organizational commitment, followed by work values and self-actualization. The best-fit SEM demonstrated strong alignment among these factors, explaining 75.1% of the variance in organizational commitment. The findings emphasized the importance of creating supportive work environments that aligned with employee values, promoted personal growth, and enhanced job satisfaction to cultivate a dedicated and effective workforce.

The hyper-globalized economy reveals profound systemic vulnerabilities, as evidenced by a 5.3% decline in global merchandise trade in 2020 (WTO, 2021) and a 45% reduction in U.S. beef production capacity (USDA, 2020). Moving beyond conventional economic analysis, this paper argues that the Gandhian principle of Swadeshi (local self-sufficiency), reinterpreted through the lens of social responsibility as a strategy for decentralized economic antifragility, offers a robust framework for resilience that intrinsically prioritizes community well-being and ecological balance. Using a mixed-methods approach—a comparative case study and fixed-effects panel regression analysis of Indian district-level data (2015–2022)—this study finds that a one-unit increase in the Regional Self-Sufficiency Index (RSSI) corresponds to a significant 0.32-unit decrease in price volatility during disruptions (β = -0.32, p = 0.015, 95% CI [-0.58, -0.06]). The model indicates that a 15% increase in regional self-sufficiency could reduce disruption impact by 27–38%. Policy implications, framed through a social responsibility perspective, include the implementation of "Social Resilience Budgets" mandating public procurement from bio-regional social enterprises and the creation of green credit lines for local cooperatives.

Artificial Intelligence (AI) has rapidly integrated into various aspects of college life, significantly transforming the educational landscape. This abstract provides an overview of the diverse applications of AI in education related contexts, highlighting its potential to enhance learning experiences, administrative efficiency, and campus life. AI-driven educational tools, such as intelligent tutoring systems and personalized learning platforms, tailor instructional content to meet individual student needs, thereby fostering a more engaging and effective learning environment. These systems utilize machine learning algorithms to analyze student performance and adaptively recommend resources, exercises, and feedback, ensuring that each learner can progress at their own pace. AI applications extend to campus security and resource management as well. Intelligent surveillance systems and predictive maintenance tools contribute to a safer and more sustainable campus environment and play a crucial role in fostering inclusivity, with technologies designed to support students with disabilities through adaptive learning aids and accessible content. In addition to academic support, and it is revolutionizing administrative operations within colleges. Automated systems for admissions, scheduling, and student services streamline processes, reduce administrative burden, and improve accuracy. AI-powered chatbots and virtual assistants provide instant responses to student inquiries, facilitating better communication and support for both prospective and current students moreover, it enhances research capabilities by offering advanced data analysis tools, enabling scholars to conduct complex studies and derive meaningful insights more efficiently. AI’s role in predictive analytics assists in identifying at-risk students, allowing for timely interventions that improve retention rates and 21st century academic success.

This study explores the relationship between students’ attitude, problem-solving skills, and achievement in mathematics among secondary school students of Vijayapur city. The descriptive survey method was used to analyze students’ overall attitude towards mathematics learning. Data were collected from 800 students and analyzed using frequency distribution, mean, and standard deviation (SD). The results revealed that the mean attitude score was 85.35, with an SD of 25.89. About 58.63 % of the students exhibited scores above the mean, indicating a favorable attitude towards mathematics learning, while 41.37 % scored below the mean. These findings suggest that the majority of secondary school students of Vijayapur have positive attitudes toward mathematics learning, which is a significant predictor of their problem-solving skills and academic success.

This case report describes the management of a lumbar spine injury using Kati Basti, Matra Basti and Abhyanga. Spinal injuries often lead to low back pain, radiculopathy, and varying degrees of motor or sensory loss in the lower limbs. Ayurvedic therapies, especially Basti and Abhyanga, are commonly used for conditions driven by aggravated Vata. A 32-year-old male presented with acute lumbar pain radiating to both lower limbs after trauma. He had reduced motor strength, sensory deficits, and difficulty walking. The initial assessment included VAS for pain, neurological examination, the straight leg raising test, and the Oswestry Disability Index. MRI of the lumbar spine showed L4–L5 posterolateral disc herniation with L5 vertebral compression fracture and canal compromise. Treatment included daily Abhyanga to the lumbar region and lower limbs for 25 to 30 minutes, followed by mild Nadi Svedana. Kati Basti and Matra Basti was given according to the classical method, using Mahanarayan oil. Over 14 days, the patient received two sessions of Kati Basti morning and evening and Matra Basti after food in the morning, with regular monitoring of neurological status and vital signs. The patient reported steady improvement in symptoms. Pain decreased (VAS 8 to 2), muscle strength improved (right knee extension from MRC grade II to IV), and functional capacity increased (ODI from 70% to 20%). No adverse events were observed. A one-month follow-up showed that the improvements were maintained. This case suggests the potential benefit of combining Kati Basti and Matra Basti with Abhyanga in selected spinal injury cases and highlights the need for controlled studies.